Efficient Substring Pattern Matching Technique for Hindi Language Text

Authors

  • Barkha Sahu

Keywords:

Pattern, Substring Searching, Unicode ,Hindi Language Processing, String Searching, Substring Matching, Computational Linguistics, Pattern Detection

Abstract

With the exponential growth of internet users, the demand for regional language support, particularly Hindi, has significantly increased. However, the digital ecosystem remains predominantly optimized for the English language, resulting in a subpar experience for native Hindi users. Addressing this gap necessitates the development of efficient computational techniques tailored for Hindi language processing. One of the critical challenges in this domain is efficient string searching, which forms the basis for numerous applications such as text retrieval, data mining, and natural language processing. This research presents a novel substring searching algorithm specifically designed for the Hindi language. The proposed approach focuses on minimizing the number of character comparisons required to locate a pattern within a given string, thereby improving search efficiency and overall computational performance. By leveraging the unique characteristics of the Hindi script and optimizing the search mechanism accordingly, our algorithm enhances processing speed while maintaining high accuracy. This advancement not only contributes to the field of computational linguistics for Hindi but also promotes broader inclusion of regional languages in digital platforms, ensuring a more equitable and seamless user experience for the growing base of Hindi-speaking internet users.

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References

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Published

27.12.2022

How to Cite

Barkha Sahu. (2022). Efficient Substring Pattern Matching Technique for Hindi Language Text. International Journal of Intelligent Systems and Applications in Engineering, 10(3s), 411 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7730

Issue

Vol. 10 No. 3s (2022)

Section

Research Article

License

Creative Commons License

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